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粮食安全问题一直倍受世界各国关注,及时、准确地了解其他国家或地区的粮食生产状况,对于中国粮食贸易和粮食宏观调控,具有十分重要的意义。本文以美国冬小麦和玉米为研究对象,在分析各作物空间分布及生长季节的基础上,利用土地利用数据剔除非耕地信息,使提取的归一化植被指数(NDVI)客观地反映各作物的生长状况。以1998—2007年的SPOTVEGETATION旬最大值合成NDVI资料为数据源,研究了美国玉米和小麦生长季的旬NDVI与产量的关系,确定了不同月份的建模因子,分别建立了美国玉米和冬小麦不同月份的产量动态预报模型。通过对各模型估算产量与实际产量进行比较,各模型预报结果的相对误差大部分在3%以内,精度较高,说明建立的作物产量动态预报模型实用可行,能够投入产量预报业务应用。
The issue of food security has drawn much attention from countries all over the world. It is of great significance for China to understand the status of food production in other countries and regions in a timely and accurate manner for the grain trade in China and the macro-control of grain. Based on the analysis of the spatial distribution and growing season of each crop, this paper excluded the information of non-cultivated land using the land use data to make the extracted normalized vegetation index (NDVI) objectively reflect the growth of each crop situation. Taking NDVI data from the maximum of ten days of SPOTVEGETATION from 1998 to 2007 as the data source, the relationship between the ten-day NDVI of maize and wheat growing season and the yield was studied. The modeling factors of different months were determined, Monthly production forecasting model. By comparing the estimated output with the actual output of each model, the relative errors of the results of each model are mostly within 3% and the accuracy is high, which shows that the established dynamic model of crop yield is practical and feasible and can be applied to the production forecasting business.